A Study on Knowledge Extraction Methods from Equipment Maintenance Documents

On "deep" knowledge extraction from documents

SYNDIKATE comprises a family of natural language understanding systems for automatically acquiring knowledge from real-world texts (e.g., information technology test reports, medical finding reports), and for transferring their content to formal representation structures which constitute a corresponding text knowledge base. We present a general system architecture which integrates requirements ...

Automatic knowledge extraction from documents

extraction from documents J. Fan A. Kalyanpur D. C. Gondek D. A. Ferrucci Access to a large amount of knowledge is critical for success at answering open-domain questions for DeepQA systems such as IBM Watsoni. Formal representation of knowledge has the advantage of being easy to reason with, but acquisition of structured knowledge in open domains from unstructured data is often difficult and e...

Cultural Heritage: Knowledge Extraction from Web Documents

This article presents the use of NLP techniques (text mining, text analysis) to develop specific tools that allow to create linguistic resources related to the cultural heritage domain. The aim of our approach is to create tools for the building of an online “knowledge network”, automatically extracted from text materials concerning this domain. A particular methodology was experimented by divi...

Automatic Extraction of Knowledge from Web Documents

A large amount of digital information available is written as text documents in the form of web pages, reports, papers, emails, etc. Extracting the knowledge of interest from such documents from multiple sources in a timely fashion is therefore crucial. This paper provides an update on the Artequakt system which uses natural language tools to automatically extract knowledge about artists from m...

Topic Extraction based on Prior Knowledge obtained from Target Documents